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                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
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<div class="textblock">Here is a list of all functions with links to the classes they belong to:</div>

<h3><a id="index_a" name="index_a"></a>- a -</h3><ul>
<li>AbsoluteLoss()&#160;:&#160;<a class="el" href="classshark_1_1_absolute_loss.html#a61e08fc516ca03b3a7ddd57288a2202f">shark::AbsoluteLoss&lt; VectorType &gt;</a></li>
<li>AbstractBudgetMaintenanceStrategy()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_budget_maintenance_strategy.html#a2a6d7afdbb1e6dc61f86619dd526a544">shark::AbstractBudgetMaintenanceStrategy&lt; InputType &gt;</a></li>
<li>AbstractKernelFunction()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_kernel_function.html#a81ed7e2e580d7967ba21d82cf8105c4c">shark::AbstractKernelFunction&lt; InputTypeT &gt;</a></li>
<li>AbstractLinearSvmTrainer()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_linear_svm_trainer.html#aef1e11708ae6adc64c75243cbc5acb89">shark::AbstractLinearSvmTrainer&lt; InputType &gt;</a></li>
<li>AbstractLineSearchOptimizer()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_line_search_optimizer.html#ac31b2a22776918a63312376f198e9968">shark::AbstractLineSearchOptimizer&lt; SearchPointType &gt;</a></li>
<li>AbstractLoss()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_loss.html#aae8049c358e6ccfece94d4a978306c4c">shark::AbstractLoss&lt; LabelT, OutputT &gt;</a></li>
<li>AbstractMetric()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_metric.html#aeb00f4cd45e33127a8e0580aa8f1e6f0">shark::AbstractMetric&lt; InputTypeT &gt;</a></li>
<li>AbstractModel()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_model.html#a0b7aeb13b70c8d4cffc4958e6583627c">shark::AbstractModel&lt; InputTypeT, OutputTypeT, ParameterVectorType &gt;</a></li>
<li>AbstractObjectiveFunction()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_objective_function.html#a0f32ae97885db58f9602191d64284f98">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a></li>
<li>AbstractSvmTrainer()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_svm_trainer.html#aab27c6424184668af4f785f525ca3a84">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a></li>
<li>accessCount()&#160;:&#160;<a class="el" href="classshark_1_1_qp_config.html#a240e6aeb51dee3764a4ee3962e0ff7e0">shark::QpConfig</a></li>
<li>accuracy()&#160;:&#160;<a class="el" href="classshark_1_1_lasso_regression.html#a9b0659679b615f23713ac8a3669e6de1">shark::LassoRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_logistic_regression.html#a08948cf00fbe0ae3263449ca3f49ab36">shark::LogisticRegression&lt; InputVectorType &gt;</a></li>
<li>Ackley()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_ackley.html#ac7f2edc3a1163a71d0e47ef3f1820d33">shark::benchmarks::Ackley</a></li>
<li>activateVariable()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_problem.html#a3e70b06e9879ac5d14192b7b1ed551c9">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#a0c80f38017ca75c1b2a6bc3654e0b627">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>activationFunction()&#160;:&#160;<a class="el" href="classshark_1_1_conv2_d_model.html#af5b1b148205a549e9fd13fba87d5ad62">shark::Conv2DModel&lt; VectorType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#ac51bc24c8a03f67237bf7f10ed4e0894">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a></li>
<li>active()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_problem.html#a0541d4c711a6d82bf2063d9cf030e551">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#a1e36b705c5de7db9cc1a9882753d8102">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>activeUpdate()&#160;:&#160;<a class="el" href="classshark_1_1_elitist_c_m_a.html#a5a3da54f1bf2d73e7a96f140e3e91f61">shark::ElitistCMA</a></li>
<li>Adam()&#160;:&#160;<a class="el" href="classshark_1_1_adam.html#a5710b74b45246dc8edbc377ecaf0292a">shark::Adam&lt; SearchPointType &gt;</a></li>
<li>adaptationFrequency()&#160;:&#160;<a class="el" href="classshark_1_1_r_v_e_a.html#af69164a51c9b14e1bd54c811f0f48134">shark::RVEA</a></li>
<li>add()&#160;:&#160;<a class="el" href="classshark_1_1_combined_objective_function.html#afadaacaa1f93c32f2345c422710685ee">shark::CombinedObjectiveFunction&lt; SearchPointType, ResultT &gt;</a>, <a class="el" href="classshark_1_1_concatenated_model.html#a1131fcd2324b57789ff7239b7236294e">shark::ConcatenatedModel&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_qp_sparse_array.html#a3e824fc525e7c61c28b01158f778fb81">shark::QpSparseArray&lt; QpFloatType &gt;</a></li>
<li>add_scaled()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_linear.html#a64edc8279169777bf9ef05052a412acd">shark::QpMcLinear&lt; InputT &gt;</a></li>
<li>addClass()&#160;:&#160;<a class="el" href="classshark_1_1_one_versus_one_classifier.html#a5ded346e1b9354472fdfe9eb35a6023f">shark::OneVersusOneClassifier&lt; InputType, VectorType &gt;</a></li>
<li>addDeltaLinear()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_box_decomp.html#a3ac7767ba5e2c3d50301aea5fcb30f43">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#a4ec3b3bf8b8dc4d6861ac2f8756575d8">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
<li>addKernel()&#160;:&#160;<a class="el" href="classshark_1_1_product_kernel.html#ae1a781a38a1a31476a4308280a0d3ea4">shark::ProductKernel&lt; InputType &gt;</a></li>
<li>addModel()&#160;:&#160;<a class="el" href="classshark_1_1_ensemble.html#aaa96d4139d33b84477f8a41d9d12c8bb">shark::Ensemble&lt; ModelType, OutputType &gt;</a></li>
<li>addStatistic()&#160;:&#160;<a class="el" href="structshark_1_1statistics_1_1_statistics.html#ab958ce0475386d433f26998225c7c4c8">shark::statistics::Statistics&lt; Parameter &gt;</a></li>
<li>addToModel()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_budget_maintenance_strategy.html#a763d8224ee45bb2bb727cb05ac002b94">shark::AbstractBudgetMaintenanceStrategy&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_merge_budget_maintenance_strategy_3_01_real_vector_01_4.html#a26faf1b7720149479335a6cf8aeebb38">shark::MergeBudgetMaintenanceStrategy&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_project_budget_maintenance_strategy.html#a2c1ffe6ed6921945f7e9b955baf1b0cf">shark::ProjectBudgetMaintenanceStrategy&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_project_budget_maintenance_strategy_3_01_real_vector_01_4.html#a716c4803d4a64e0e30ef4d57032ed5d9">shark::ProjectBudgetMaintenanceStrategy&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_remove_budget_maintenance_strategy.html#a795f1710e6f333fcf7c7baad2e7bcc54">shark::RemoveBudgetMaintenanceStrategy&lt; InputType &gt;</a></li>
<li>alpha()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_cigar.html#a36582f2e9e6c15cfadaecf47d9aaaa9e">shark::benchmarks::Cigar</a>, <a class="el" href="classshark_1_1benchmarks_1_1_cigar_discus.html#a60e96d8546b196dea69e0b2299f77723">shark::benchmarks::CigarDiscus</a>, <a class="el" href="structshark_1_1benchmarks_1_1_discus.html#ae02ec221dc77f717f65f99e6f2fe2aa5">shark::benchmarks::Discus</a>, <a class="el" href="classshark_1_1_box_constrained_problem.html#ae0e263a6f4ea23985dd6e4b658e0a047">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_kernel_expansion.html#a3c65dfd17f38eaa461f6400d302fae48">shark::KernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_box_decomp.html#a3534431d3320ea945bf59be4b6287133">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_r_v_e_a.html#a8c6b046bd8c02578d5d6e07510997806">shark::RVEA</a>, <a class="el" href="classshark_1_1_svm_problem.html#a97a8afab15ad38ec1fb321317f9454a1">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>announceConstraintHandler()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_objective_function.html#a2b1a8af419059a542cb3d0848dd278a2">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a></li>
<li>append()&#160;:&#160;<a class="el" href="group__shark__globals.html#ga55cb071b82f9cfd984a855eddb9bf51e">shark::Data&lt; Type &gt;</a>, <a class="el" href="group__shark__globals.html#ga3c9be5eff818d2c5eb10b35f7b47ee14">shark::LabeledData&lt; InputT, LabelT &gt;</a></li>
<li>applyStep()&#160;:&#160;<a class="el" href="classshark_1_1_svm_problem.html#aca60a43765c528fb1e2e5a5acb495de8">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>approximationDelta()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_calculator.html#a089a678e12c3772b6e50abab495bdcc6">shark::HypervolumeCalculator</a>, <a class="el" href="structshark_1_1_hypervolume_contribution.html#ad69390eb1fc2b938ab7c4e75b29a07de">shark::HypervolumeContribution</a>, <a class="el" href="structshark_1_1_hypervolume_indicator.html#a8e06f7dec5c62471fd105e6609442bb4">shark::HypervolumeIndicator</a></li>
<li>approximationEpsilon()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_calculator.html#a3ad379a89066eb0490896b3d2a2415b8">shark::HypervolumeCalculator</a>, <a class="el" href="structshark_1_1_hypervolume_contribution.html#a256082b054ca17a3bf55857dc0513975">shark::HypervolumeContribution</a>, <a class="el" href="structshark_1_1_hypervolume_indicator.html#a5e0a00ec4eec8371553fd6971352212e">shark::HypervolumeIndicator</a></li>
<li>approxMu()&#160;:&#160;<a class="el" href="classshark_1_1_r_v_e_a.html#af00048a74be3db8fb273ba0cfb01de6a">shark::RVEA</a></li>
<li>ARDKernelUnconstrained()&#160;:&#160;<a class="el" href="classshark_1_1_a_r_d_kernel_unconstrained.html#aec9b075b05db8e7c15ba3ce4f9ad6d1d">shark::ARDKernelUnconstrained&lt; InputType &gt;</a></li>
<li>assignExponentialRange()&#160;:&#160;<a class="el" href="classshark_1_1_grid_search.html#a9f7f3ace7fa5ad50b430ee33104e5fbc">shark::GridSearch</a></li>
<li>assignLinearRange()&#160;:&#160;<a class="el" href="classshark_1_1_grid_search.html#a13c9339693b4c33f25a1842ca09aaea3">shark::GridSearch</a></li>
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